Fig. 1.

The main framework of multi-view deep learning fusion model. We firstly extracted the lung region in CT slices using threshold segmentation method. Then, we trained our model based on the architecture of ResNet50. The inputs of the model are the corresponding CT images in axial, coronal, and sagittal views that selected from the maximum lung region selection. The three branch networks output feature maps that aggregated to feed into a fully connected dense layer. Finally, the layer outputs the risk value of COVID-19 pneumonia to evaluate the performance of the deep learning model.